3 papers
cs.AI2026
EvoThink: Evolving Thinking in Large Reasoning Models via Self-Pruning and Aha-Moment Preference Optimization
Xinbang Dai, Zheyu Xin, Huikang Hu +7
Large Reasoning Models (LRMs) often suffer from overthinking due to redundant verification steps. Existing approaches for mitigating overthinking, such as fast-slow thinking switch…
cs.AI2026
KG2Code: Bridging Knowledge Graphs and Large Language Models via Executable Code for Question Answering
Yike Wu, Nan Hu, Guilin Qi +11
Recent research has explored the integration of knowledge graphs (KGs) with large language models (LLMs) to enhance their performance on downstream knowledge-intensive tasks, parti…
cs.AI2025
Can LLMs Solve ASP Problems? Insights from a Benchmarking Study (Extended Version)
Lin Ren, Guohui Xiao, Guilin Qi +2
Answer Set Programming (ASP) is a powerful paradigm for non-monotonic reasoning. Recently, large language models (LLMs) have demonstrated promising capabilities in logical reasonin…